Final answer:
The random variable X represents the number of dice that match a player's bet in the game. The values of X can be 0, 1, 2, or 3, with a Binomial distribution X ~ B(3, 1/6). The average expected number of matches and profit can be calculated from the PDF table and are used to assess the house's advantage in the game.
Step-by-step explanation:
Let X be the random variable representing the number of matches (between the dice roll and the player's bet) in the described games. The values that X may take on are 0, 1, 2, or 3, with respective probabilities based on the roll of three fair six-sided dice or pictorial dice.
Distribution of X
X follows a Binomial distribution, since there are a fixed number of independent trials (three dice rolls), two outcomes (match or no match), and the probability of a match is the same for each roll. The probability of a match is 1/6, and the probability of no match is 5/6. Therefore, the distribution is X ~ B(3, 1/6).
Values for Y and PDF Table
The values that Y, the profit per game, may take on are -1, 1, 2, or 3 dollars. The PDF table is constructed by calculating the probabilities for 0, 1, 2, or 3 matches and associating them with the corresponding profits.
Expected Number of Matches and Profit
The average expected number of matches (E(X)) over the long run is calculated using the formula for the expected value of a binomial distribution. Similarly, the average expected profit (E(Y)) can be calculated using the expected number of matches and associated profit values.
House Advantage
To determine who has the advantage in this game, we calculate the expected profit for the player and compare it to the amount the house is expected to retain. An expected profit less than zero indicates a house advantage.